Signal Backtesting Engine
Build a flexible backtesting engine for testing trading strategies on historical data.
Educational example only. Not investment advice. Test on paper or sandbox accounts. You are responsible for how you run it and for each data provider's terms. Code and data are provided "as is" and may contain errors. Terms & Disclaimer
Tech Stack
Steps
- 1
Set up Python environment with required packages
- 2
Fetch historical data using yfinance or Alpha Vantage
- 3
Create a Strategy base class with buy/sell signal methods
- 4
Implement backtesting logic: iterate through data, track positions, calculate P&L
- 5
Add transaction costs, slippage, and position sizing
- 6
Calculate performance metrics: Sharpe ratio, max drawdown, win rate
- 7
Visualize equity curve, drawdowns, and monthly returns with Matplotlib
- 8
Export results to CSV and generate a tearsheet report